[WIP] Multimodal model support for V1 TPU

[mgoin]

Based on and requires #11936

Currently only focused on usability and correctness, not performance.

This does not deal with pre-compiling the encoder forward pass, so in the event that the model is passed in image/video/audio that is a new shape, it will force compilation during runtime.

Tested Examples

Image:

VLLM_USE_V1=1 python llava_tpu.py
...
Prompt 1: What do you see in this image?
Response:  The image features a tall tower with a spire, surrounded by a beautiful cherry blossom tree. The tree is filled with pink flowers, creating a stunning contrast against the tower. The blossoms are scattered throughout the tree, with some closer to the top and others near the bottom. The scene

Prompt 2: What colors are most prominent in this image?
Response:  The most prominent colors in this image are pink and white, as they are associated with the cherry blossoms and the sky.

Audio:

VLLM_USE_V1=1 python examples/offline_inference/offline_inference_audio_language.py --model-type qwen2_audio
Processed prompts: 100%|████████████████████████████████████| 1/1 [00:33<00:00, 33.90s/it, est. speed input: 12.80 toks/s, output: 1.42 toks/s]
The recited content in the audio is: 'First words I spoke in the original coronavirus a little feat of practical poetry Mary had a little lamb its fleece was white as snow and everywhere that Mary went the lamb was sure to go.'

[github-actions]

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🚀

[robertgshaw2-redhat]

cc @bvrockwell - FYI

[mergify]

This pull request has merge conflicts that must be resolved before it can be
merged. Please rebase the PR, @mgoin.

https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/working-with-forks/syncing-a-fork

[bvrockwell]

cc @yaochengji could you please take a look?